0000000000400180

AUTHOR

Helder Pinto

0000-0002-0455-6466

showing 5 related works from this author

Assessing Transfer Entropy in cardiovascular and respiratory time series: A VARFI approach

2021

In the study of complex biomedical systems represented by multivariate stochastic processes, such as the cardiovascular and respiratory systems, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. Recently, the quantification of multiscale complexity based on linear parametric models, incorporating autoregressive coefficients and fractional integration, encompassing short term dynamics and long-range correlations, was extended to multivariate time series. Within this Vector AutoRegressive Fractionally Integrated (VARFI) framework formalized for Gaussian processes, in this work we propose to estimate the Transfer Entropy, or equivalently G…

symbols.namesakeAutoregressive modelDynamical systems theoryGranger causalityComputer scienceStochastic processPhysics::Medical PhysicsParametric modelsymbolsTransfer entropyStatistical physicsGaussian processSystem dynamicsProceedings of Entropy 2021: The Scientific Tool of the 21st Century
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Multiscale partial information decomposition of dynamic processes with short and long-range correlations: theory and application to cardiovascular co…

2022

Abstract Objective. In this work, an analytical framework for the multiscale analysis of multivariate Gaussian processes is presented, whereby the computation of Partial Information Decomposition measures is achieved accounting for the simultaneous presence of short-term dynamics and long-range correlations. Approach. We consider physiological time series mapping the activity of the cardiac, vascular and respiratory systems in the field of Network Physiology. In this context, the multiscale representation of transfer entropy within the network of interactions among Systolic arterial pressure (S), respiration (R) and heart period (H), as well as the decomposition into unique, redundant and s…

FOS: Computer and information sciencesmultivariate time seriesPhysiologyEntropyRespirationBiomedical EngineeringBiophysicsheart rate variabilitytransfer entropyredundancy and synergyBlood PressureHeartQuantitative Biology - Quantitative MethodsCardiovascular SystemMethodology (stat.ME)Heart RatePhysiology (medical)FOS: Biological sciencesCardiovascular controlSettore ING-INF/06 - Bioingegneria Elettronica E Informaticavector autoregressive fractionally integrated (VARFI) modelsHumansQuantitative Methods (q-bio.QM)Statistics - MethodologyPhysiological measurement
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Frequency Domain Information Decomposition: Application to Plateau Waves of Intracranial Pressure

2022

The sustainment and/or resurgence of Plateau Waves (PWs) reveals a borderline cerebral situation of the pressure-volume relationship and is related to increased mortality. The intense systemic stress caused by PWs can be evidenced by the study of Heart Rate Variability (HRV), which is an indicator of the activity of the autonomic nervous system, namely the sympathetic and parasympathetic imbalance. In this work, heart and brain crosstalk interactions will be analyzed using a spectral decomposition of multivariate information measures, which provides frequency-specific quantification of the information shared between a target and two source time series. The spectral measures of information h…

Information theoryinformation decompositionLinear parametric modelling2022 12th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO)
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Assessing Transfer Entropy in cardiovascular and respiratory time series under long-range correlations.

2021

Heart Period (H) results from the activity of several coexisting control mechanisms, involving Systolic Arterial Pressure (S) and Respiration (R), which operate across multiple time scales encompassing not only short-term dynamics but also long-range correlations. In this work, multiscale representation of Transfer Entropy (TE) and of its decomposition in the network of these three interacting processes is obtained by extending the multivariate approach based on linear parametric VAR models to the Vector AutoRegressive Fractionally Integrated (VARFI) framework for Gaussian processes. This approach allows to dissect the different contributions to cardiac dynamics accounting for the simultane…

Time FactorsTransfer entropyHeart RateEntropySettore ING-INF/06 - Bioingegneria Elettronica E InformaticaHumansHeartVector AutoRegressive Fractionally Integrated (VARFI) modelCardiovascular Systemlong-range correlationAnnual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
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Assessing Transfer Entropy in cardiovascular and respiratory time series: A VARFI approach

2021

In the study of complex biomedical systems represented by multivariate stochastic processes, such as the cardiovascular and respiratory systems, an issue of great relevance is the description of the system dynamics spanning multiple temporal scales. Recently, the quantification of multiscale complexity based on linear parametric models, incorporating autoregressive coefficients and fractional integration, encompassing short term dynamics and long-range correlations, was extended to multivariate time series. Within this Vector AutoRegressive Fractionally Integrated (VARFI) framework formalized for Gaussian processes, in this work we propose to estimate the Transfer Entropy, or equivalently G…

vector autoregressive fractionally integrated (VARFI) modelSettore ING-INF/06 - Bioingegneria Elettronica E Informaticasystolic arterial pressure (SAP)Multi-scale entropy (MSE)heart rate variability (HRV)
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